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Record W2158555411 · doi:10.1177/0047287509349268

French versus Canadian Tourism: Response to the Disabled

2009· article· en· W2158555411 on OpenAlexaboutno aff
Ina Freeman, Noureddine Selmi

Bibliographic record

VenueJournal of Travel Research · 2009
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsnot available
Fundersnot available
KeywordsTourismAccommodationDestinationsPerspective (graphical)Disabled peopleRank (graph theory)PopulationTourist destinationsMarketingGeographyPolitical scienceAdvertisingDemographic economicsBusinessPsychologySociologyDemographyEconomics

Abstract

fetched live from OpenAlex

Both France and Canada rank as highly developed tourist destinations. This study compares the underexplored area of the needs of tourists who are disabled in France ( n = 25) and Canada ( n = 24). The authors examine Canada’s and France’s accommodation to both domestic and international tourists who have disabilities, giving the study a unique perspective in comparing and contrasting results to the same questions across similar populations in two countries. The results indicate that neither country’s tourism industry has developed an effective policy to accommodate tourists who have disabilities indicated by significant barriers existing that exclude segments of the disabled population. This article takes the words of those with disabilities to recommend steps necessary to improve the tourism opportunities with this population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.119
GPT teacher head0.440
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations57
Published2009
Admission routes1
Has abstractyes

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